Environment and Planning B: Urban Analytics and City Science

In 1977 Christopher Alexander and his colleagues from the Centre for Environmental Structure published A Pattern Language, an innovative design guide aimed at restoring life and beauty to the built environment. Since then, A Pattern Language has become one of the most widely read architectural treatises ever published. However, despite its popularity, the structure of A Pattern Language remains poorly understood. In response to this situation, this paper uses graph theory to examine Alexander’s language including the entire set of 253 patterns and over 1800 relationships between them. Through this mathematical analysis the paper tests two hypotheses about the ‘invariant patterns’ Alexander was most confident in. The first hypothesis tests whether invariant patterns occupy more prominent positions within the language, and the second tests whether invariant patterns form a core structure within the language that supports less developed patterns. Through this process the paper illuminates several previously unconsidered aspects of the structure of A Pattern Language while providing the first graphic representation of the entire underlying structure that unites the individual patterns into a coherent language.

Urban designers find it virtually impossible to (re)construct self-organising urban fabric formed by a synthesis of various builders. Here we show how generic, bottom-up grammars represent historic urban fabric in a unique context, and how shape rules are embedded in the evolutionary context. This paper generalises and formalises a context-free grammar and a context-sensitive grammar to describe and design two broadly categorised (i.e. orthogonal and non-orthogonal) urban patterns. Both grammars are constructive and employ morphological parameters to govern the patterning towards a desired form. The context-free grammar describes the density and aggregation of built forms while the context-sensitive grammar represents the interactions between streets and plots. Both grammars were applied to preserve the figure-ground relationship and proved effective in designing complex urban fabric.

Estimating residential building energy use across large spatial extents is vital for identifying and testing effective strategies to reduce carbon emissions and improve urban sustainability. This task is underpinned by the availability of accurate models of building stock from which appropriate parameters may be extracted. For example, the form of a building, such as whether it is detached, semi-detached, terraced etc. and its shape may be used as part of a typology for defining its likely energy use. When these details are combined with information on building construction materials or glazing ratio, it can be used to infer the heat transfer characteristics of different properties. However, these data are not readily available for energy modelling or urban simulation. Although this is not a problem when the geographic scope corresponds to a small area and can be hand-collected, such manual approaches cannot be easily applied at the city or national scale. In this article, we demonstrate an approach that can automatically extract this information at the city scale using off-the-shelf products supplied by a National Mapping Agency. We present two novel techniques to create this knowledge directly from input geometry. The first technique is used to identify built form based upon the physical relationships between buildings. The second technique is used to determine a more refined internal/external wall measurement and ratio. The second technique has greater metric accuracy and can also be used to address problems identified in extracting the built form. A case study is presented for the City of Nottingham in the United Kingdom using two data products provided by the Ordnance Survey of Great Britain: MasterMap and AddressBase. This is followed by a discussion of a new categorisation approach for housing form for urban energy assessment.

The integration of input–output and econometric models at regional level has gained popularity for its superior performance in forecasting employment and examining the impacts of policies. There are a number of approaches to integrate the two models. This paper examines the integration of input–output with econometric modelling using two merging methodologies, namely coupling and holistic embedding. Each methodology is analysed with respect to the accuracy of its results of total and sectoral employment forecasting. Both methodologies are applied to a regional economy in Australia. The methodology which shows superior forecasting accuracy is applied to examine the significance of sectors that generate the highest number of employments relative to other sectors.

This study examines whether compact development promotes a seismic-resistant city. A statistical model is used to simulate seismic damages under four spatial structure scenarios for Taichung, Taiwan. The existing floor areas of various land uses are allowed to be reallocated for reshaping the spatial structure of the city. This provides an opportunity to find an urban structure that would best resist seismic impacts similar to what have occurred during the past 100 years. The results suggest a polycentric compact form for seismic mitigation. This form, derived from the vision of Taichung, would have less seismic damages by shifting floor areas from the city center to three proposed subcenters, far away from most seismic impacts. One weakness is the seismic impacts from the north. The results also reveal that a monocentric compact form would incur more damages because the downtown area is essentially seismic-vulnerable. This paper advocates the application of a stricter building code in the downtown area. The local government should also not render additional building bulk as an incentive for urban renewal.

Urban compaction policies have been widely adopted in developed countries in pursuit of more sustainable cities. Compactness is achieved through a process of ‘densification’, of developing and using land and buildings more intensively. However, empirical evidence on the processes and outcomes of urban densification is lacking. The paper addresses this lacuna. It considers densification in England, a country that has long experience of applying policies of urban containment and consolidation; and one where new data sources allow the analysis of recent land use change at a level of detail not hitherto possible. In England between 2001 and 2011, the bulk of additional dwellings were accommodated within urban areas, increasing their density. Yet, there were wide inter- and intra-regional variations in the pattern of densification: for example, in the contributions of large scale, formal development and of small scale, informal, gradual change – of ‘hard’ and ‘soft’ densification – to the process. The significant differences in local experiences of densification that result raise major issues for policy.

The excess commuting framework has advanced a series of metrics through which a city or a region’s jobs-housing balance and commuting efficiency can be measured. This study seeks to add to the conceptual development and extension of the excess commuting framework. Specifically, it considers the carrying capacity (of links) and related congestion issues in the excess commuting framework and demonstrates that overlooking these characteristics has important implications for excess commuting metrics. Drawing on an empirical case study, it shows that when carrying capacity and traffic congestion are accounted for, the observed commute is longer than otherwise. Excess commuting tends to be higher than its counterparts in previous excess commuting studies. The findings suggest that future excess commuting studies should take account of carrying capacity and congestion in determining excess commuting metrics. Moreover, high-quality connections (preferably via public transport) between jobs and housing allied with sufficient carrying capacity of popular links/routes for commuters are crucial preconditions for cities and regions to harvest the full benefits of jobs-housing balance policies targeted at the reduction of the average commute distance and vehicle miles travelled.

We describe a simple spatial model of urban growth for systems of cities at the macroscopic scale, which combines direct interaction between cities and an indirect effect of physical network flows as population growth drivers. The model is parametrized on population data for the French system of cities between 1831 and 1999, in which strong non-stationarity in correlation patterns suggest to apply the model on local time windows. The corresponding calibration of the model using genetic algorithms provides the evolution of interaction processes and network effects in time. Furthermore, the fit improvement when adding network module appears effective when controlling for additional parameters, what confirms the ability of the model to unveil network effects in the system of cities.

This study assesses the externality of three new master-planned housing estate development projects on an old residential area in Hong Kong. Replicating the methodology of an event study, this paper presents the changes to the market values and the turnover of property transactions of the apartments in the existing neighbourhood before and after the successive completion of these three new projects over a period of 10 years. Our findings have identified a diverse picture about the impacts of these new housing estates on the neighbourhood. Positive externalities occur under specific circumstances related to the facility provision, spatial design and interfacing with the neighbourhood and background of the new projects. Housing externality does not depend only on the degree of geographical proximity. The policy implication is that urban planning can expand the positive spillover of infill redevelopment not only by replacing the urban dis-amenities by new buildings, but also through a responsive and beneficial integration of the new development with the existing neighbourhood.

Despite several calls in this journal of debating the rapid growth of the literature on “smart cities”, such a debate has in large been absent. Smart cities are often un-critically launched as a sustainable way of developing cities. When cities become increasingly complex as its features are wired into the Internet, theories for their understanding is lagging behind. As it is prospected that a greater number of people and things will become connected by Information and Computer Technology, the complexity of urban systems will over time increase. Historical insights reveal that as complexity in societies increase, growth in energy consumption tends to follow. In this paper, we discuss whether complexity carried too far could lead to diminishing returns of energy saving and create unmanageable urban systems. As part of initiating such a debate, this commentary asks whether the smart cities development has a bearing on the issue whether a society can erode its capacity of sustaining itself? We pose this question against the backdrop that no one actually knows what type of society the smart cities model in the end will generate.